Alexis
Hi everyone. Welcome to another episode of Talk Tech with Data Dave. I’m Alexis, your host of this podcast, and I’m here today with Dave to talk about his experience last week at Enterprise Data World, otherwise known as EDW.

Before we get started, I do want to remind all of our listeners out there that you can ask us a question at any time for Dave to answer by contacting us at contact at talktech@d3clarity.com. Once again, that email is talktech@d3clarity.com. We’re happy to answer your questions about all things data, all things cloud, all things technology, all things D3Clarity.

Dave, how are you this morning?

Data Dave
I’m very well, Alexis. Very well, indeed. Thank you. And thank you for introducing us so well.

Alexis
I just figured I’d get my entire spiel out of the way before I asked you the actual question. So, last week, you were at Enterprise Data World hosted by DATAVERSITY. I know you had a pretty awesome expense there. I was hoping to ask you what was like the hottest topic at EDW this year. What was everybody talking about at Enterprise Data World? But before we start, can you explain a little bit about what Enterprise Data World is so our listeners know?

Data Dave
Well, Enterprise Data World is a conference. Reasonably sized conference; about 1000 people there. Hosted, as you said, by DATAVERSITY, who are a leader in the education space around data management, data governance, and that sort of thing focused at all data professionals. largely. So it covers data warehouses, data governance, data management, a lot of the the technologies and spaces and business uses of data and using data as a whole. It was a really good conference similar to DGQ that we went to last year, and we’ll be going to again, but a little broader. A little broader in terms of not just data governance, but the broader spectrum of data.

Alexis
Okay, so the conference focused on all things data, more or less/

Data Dave
Yeah. For data management professionals.

Alexis
Perfect. Okay. And so, like I said, what was the biggest topic there? And also, like what were you doing there I guess is worth highlighting as well?

Data Dave
What was I doing there? I was there, really, to explore. I’ve never been to EDW before. It was a very good conference. I enjoyed it a lot. I was there for two or three days. I met a lot of really good people in the data management space, and who are obviously data professionals from a lot of organizations.

The reason I went there was really as an expansion from our presence at DGIQ, you know, and then checking out and seeing what the audience was like and listening to some of the speakers, especially some of the industry speakers, on what are they doing with data and how are they making it work for them.

So, that’s what I was really there for. I was not speaking at this point, but I just meant as an attendee. Just to meet with a number of people, a lot of them were old friends and people that I’ve known from different places, so that’s always fun.

So, your question was, what was the hottest topic? The hottest topic for me, by far, was probably artificial intelligence, machine learning, and decision making and how to really use those kinds of technologies and prepare the data and prepare hig- quality data for those structures. So, ChatGPT was all up there. Generative AI in general. The Microsoft one and others to, “How can you use that kind of technology to either assist in data governance or data management, as well as, to use those kinds of technologies in your industry, in your business and make sure that they’ve got the right level of data quality and the right level of structure to feed into it and to provide that level of knowledge.”

That, to me, was sort of the number one topic that was largely being discussed and with that and the sort of decision making. “ow do organizations make decisions? How do you structure that? How do you build that into your data? How can you know that your data is good for those decisions?”

Alexis
That makes total sense. Because you and I have talked about this before. The idea that, if we’re pumping bad data into AI and AI gets the answer wrong, that’s not AI’s fault. That’s our fault, because we pump that data into it. And so, making sure that your data is clean from the front is going to make the output just better overall, but also being sure we are getting the correct output.

Data Dave
Exactly.

Alexis
I think about that a lot. The idea that if our data is not- obviously our data can’t be perfect- but if our data isn’t quality enough that we’re pumping into AI, we’re going to get the wrong answer. And ChatGPT is a really good example of that. I asked it an HR question one time and it very, very confidently gave me the incorrect answer.

I was like, “Yeah, that seemed right.”

Data Dave
Yes, and there were some people there that we know, right? Anthony Algmin was there. He was speaking. And then Kathy Norman from Exxon and a few others were speaking. So, it was a good conference to get reconnected with old friends.

Alexis
Oh, awesome. That’s awesome.

Well, so, as long as we’re talking about AI and machine learning, since that was the hot topic at EDW, can you talk to me a little bit about what D3Clarity does around those topics?

Data Dave
Absolutely, we do a fair amount with machine learning and AI generally. Usually, in making sure that the data is, as we’ve talked about, flowing up in a consistent, governed, managed way and getting it ready for machine learning. While we do build models and build neural-networks reasonably often, what we spend most of our time is on the feature engineering or the preparation of that data for making sure that it can be consumed by those technologies.

Alexis
Before you go on, you said neural-networks, is that what you just said earlier?

Data Dave
Neural-networks.

Alexis
Neural-networks. What is that?

Data Dave
So, neural networks is a computer concept that mimics the human brain and human decision making process. That’s the heart of most AI these days is what we call a “deep learning neural network”.

Alexis
That makes sense, Okay, okay, cool. Thank you.

Data Dave
And this kind of made us a lot of what we call “neurons” – similar to the brain. It’s a mathematical approach and computerized approach to mimicking human decision making. And that’s where the artificial intelligence comes from.

Alexis
Makes sense. Neurons, neural pathways in your brain. Artificial Intelligence. That all makes sense now. Maybe should have put that together.

Data Dave

It’s fairly mathematical. So, a lot of the data that you prepare for that kind of processing, we have to turn into numeric and mathematical patterns versus text. And so, one of what we do is that kind of preparation, “How do you turn this discrete value textual data into data that is appropriate for machine learning? And for artificial intelligence, deep learning?”

Alexis
And we’ve definitely talked about using data governance and master data management as tools that we help provide to kind of lead the data in the right direction for use in machine learning and AI or any other things that I missed there.

Data Dave
No, you’re exactly right. It’s kind of, “Let’s make sure the data is accurate. Let’s make sure it describes what it says it’s going to describe, and then let’s manipulate it in a way that prepares it for these AI technologies so That we can feed it in and get the right answer and make sure that we’ve got the right answer.”

Alexis
Awesome, I love that.

Data Dave
So that was the main thrust of EDW. It was actually quite good on the advanced, very advanced analytics. It was much more on that side of it than we often see at DGIQ. But it was it, it was a good conference, very good.

Alexis
That’s awesome. Well, as long as we’re talking about DGIQ, we will be at DGIQ West this upcoming June and that’s in San Diego, is that correct?

Data Dave
Yep, San Diego on the beach, I believe.

Alexis
And then you are presenting at that conference for sure as well as a couple of other members of the D3Clarity team, right?

Data Dave
Yes, I think we will have three presentations I believe. And we will be having a booth there. So, we’ll have quite a good presence there this year. That’s very good.

Alexis
So, if you missed Data Dave at EDW, you can always catch him at DGIQ or you can always reach out to us and if you’re going to be there, we can set up a face to face for you to talk to Data Dave on site. That would be awesome.

Data Dave
And we will be there, with our friends from Precisely. So, we work with Precisely as one of the vendors that we us their data products. And so we will be there with our friends from Precisely this time, which we’re very excited about.

Alexis
And you guys are going to be presenting on some awesome new innovations that you worked with together, right? You’ve worked on together.

Data Dave
Yes, right, exactly. So, we’re going to be presenting jointly with them on enterprise scale for reverse engineering of applications and preparing that for master data and reference data. So that’s going to be pretty exciting. We’re very excited to be there with them.

Alexis
Yeah, that’ll be awesome.

So, definitely find Data Dave at DGIQ this upcoming June, or reach out to us. You can reach out to us at talktech@d3clarity.com. Data Dave actually has a direct e-mail as well. That’s datadave@d3clarity.com. Catch us on LinkedIn or on our website, and we’d love to set up a meeting with you to chat with Data Dave anytime. But also, if you’re going to be on-site at DGIQ West this June, that’ll be a great opportunity for you guys to sit down and talk, for you to ask him any questions you have. And also, obviously I record a podcast with Dave every week or so, but I just enjoy talking to him. So, I hope you would too.

Data Dave
Excellent. Thank you, Alexis. And yes, everybody, please please send any questions that you might have. We’re quite happy to address them or have you on to ask them, that’s always possible. So, thank you very much.

Alexis
Thanks everyone. Have a great day.

Data Dave
Thank you.